Catch Me If You Can: Identifying Fraudulent Physician Reviews with Large Language Models Using Generative Pre-Trained Transformers

Understand

The proliferation of fake reviews of doctors has potentially detrimental consequences for patient well-being and has prompted concern among consumer protection groups and regulatory bodies.

• Yet despite significant advancements in the fields of machine learning and natural language processing, there remains limited comprehension of the characteristics differentiating fraudulent from authentic reviews.
• This study utilizes a novel pre-labeled dataset of 38048 physician reviews to establish the effectiveness of large language models in classifying reviews.
• Specifically, we compare the performance of traditional ML models, such as logistic regression and support vector machines, to generative pre-trained transformer models.